Bayesian Evidence Synthesis

Bayesian evidence synthesis (BES) provides a method to aggregate support from independent studies, without a need for harmonization of the data itself. With BES, the relative probability of a set of hypotheses is evaluated for each separate dataset. Only thereafter, the relative evidence is aggregated to find out which hypothesis is supported by all datasets simultaneously and is a measure of robust support. In the papers linked to this project, I applied this procedure to aggregate evidence from multiple cohort studies.

Below you find a +/- 3-minute video that I made about a publication on BES with longitudinal data from multiple cohorts and measures.

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Marielle Zondervan-Zwijnenburg
Assistant Professor Methodology and Statistics

My ambition is to enable social science researchers to use the best methods to optimally analyze their data and answer their research questions.